Research Method II Case Studies Jaechun Kim

Today, we will discuss case studies… As many quantitative works use statistics, many qualitative studies use case studies…

Why do we conduct case studies? Practical reasons Many IR research questions are not amenable to statistical methods… Why? Problem of Small-N… What does it mean? Problem of too many variables and too few cases  Difficulty of conducting large-N statistical studies… e.g., causes of great wars; hegemon and openness of trade… cf. economics Rule of thumb - N>20 Problem of quantifying key variables… e.g., war Still, well-conducted case studies > poorly conducted statistical studies… Advantage: You can be more attentive to the details overlooked by large N-studies Inherent limitations, thouogh – you’ll never have the controls of statistical methods… (Lijhphart 1971)

Statistical method requires special training and talent…  Many works in IR adopt case studies methods…

Types of Case Studies Single Case Study (or Case Study Method (Lijhphart)) A fundamental problem of single case study (if you want to make causal inferences)? Number of cases (or observations) > number of variables Otherwise, indeterminate research design Can’t even test a single hypothesis… Heuristic value A careful in-depth study of a single case can produce good description, which was not available before… That is, a single case study can produce a very informed and focused description of a single event… Sometimes, “good description is better than bad explanation…” (KKV) Basic data-gathering operation can contribute indirectly to the theory building or testing… All in all, avoid atheoretical case study; cases are selected because of an interest in case per se  case studies of this sort have limited values…!

Your single case study can be a part of multiple case studies… of on-going research… e.g., Hypothesis: democracies seldom loses war they initiate Cases: Falkland war, First Gulf War, etc. Science is cumulative endeavor; cumulative nature of social science… Single study can never debunk a hypothesis, although it can weaken it… !!! Value of crucial (hard) case study! Think about Milner’s piece… Hypothesis confirming (evaluating) and infirming (generating) case studies (Lijphart)

You can use single case study to generate a certain hypothesis that has not been discovered previously… Deviant case analysis Studies of single cases that are known to deviate from established generalization May weaken the original hypothesis (because the case is hypothesis infirming to a certain extent) But your cannot overthrow the original hypothesis… You can suggest a modified hypothesis that may be stronger than the original one!

Rule #1, when n=1 Make as many observations as possible within the case It’s not the number of case, but the number of observations… e.g., Kohli (1987) p. 146

Process-tracing (George and McKeown, 1985) A way of making many observations… Essay question for next week: What are the major elements and usages of process-tracing? What are the advantages and limits of it? Please explain with at least two existing exemplary researches that utilized process tracing.

Comparative Case Studies or Comparative Method (Lijphart) Why compare? Can we measure democracy objectively? Rationale of “Comparative Politics” To answer a certain research question! Please try to maintain analytic focus when you do comparison… !! Method of Similarity (or Agreement) (John Stuart Mill) or Most Different Systems Approach (Przeworski and Tune)

Researchers find a set of cases as diverse as possible and try to detect what they have in common…. e.g., “regime change” literature in the 1980s and early 1990s… What is the problem of this, if you want to make causal inferences (or evaluate causal hypotheses)? Control?

Method of Differences (JSM); Most Similar Systems Approach (P&T); Comparable Case Strategy (Lijphart) Allows researchers to control other confounding variables, thereby enabling to evaluate causal hypothesis e.g., Presidentialism vs. Parliamentarism; Hypothesis: Presidentialiam  Ineffective Policymaking Cases selected? Cross-sectional comparison (think about Kohli (1987)!); Time-series comparison (comparing the same unit!) Cross-states comparison Remember? Assumption of Unit Homogeneity or its less stringent version, Constant Effect Assumption…

Problem of over-determination associated with most comparable case studies What is it? It’s difficult to find sufficiently similar cases, therefore differences will always over-determine the dependent variable… JSM advised against it! What about KKV? True that sufficiently similar cases can be seldom found, but this problem can be alleviated by smart selection of cases. For instance, think about Kohli (1987)! He studied and compared sub-national units to verify his causal hypothesis…